Swiftide

Swiftide is built for Rust developers who want maximum performance and minimal overhead when building LLM applications. Its streaming pipeline architecture lets you index, transform, and query data asynchronously, which makes it a strong choice for production RAG systems. The agent framework is straightforward: define tools with a macro, hook into lifecycle events, and run queries. Integrations with Qdrant, OpenAI, FastEmbed, and others (including Groq, AWS Bedrock, Redis, Spider) give you flexibility. When should you pick Swiftide? If you're building in Rust and need to process large datasets with low latency, Swiftide shines. Its parallel pipelines can handle indexing at scale, and the query pipeline with subquestion generation improves retrieval quality. The library is actively used in production as part of Bosun.ai. When should you pass? If you're not a Rust developer, Swiftide isn't for you—it's a library, not a managed service. There's no GUI, no CLI, and you'll need to write Rust code to use it. Also, if you need built-in user management, authentication, or a hosted solution, look elsewhere. Compared to alternatives like LlamaIndex (Python) or Haystack (Python), Swiftide offers better performance but a steeper learning curve. It's not as feature-rich out of the box, but its minimal abstractions make it easy to build custom components. In practice, we'd reach for Swiftide when we're already in the Rust ecosystem and need a fast, reliable RAG pipeline. The lack of a pricing page is fine—it's free and open source under the MIT license. Just be prepared to implement your own persistence, hosting, and scaling.